Digital video products and services and devices for storage and retrieval of video streams on the Internet are ubiquitous in the marketplace. Due to limitations in digital signal storage capacity and limitations in network and broadcast bandwidth, compression of digital video signals is essential to digital video storage and transmission. As a result, many standards for compression and encoding of digital video signals, such as MPEG-2 and MPEG-4, have been promulgated. These standards specify with particularity the form of encoded digital video signals and how such signals are to be decoded for presentation to a viewer.
Video preprocessing techniques may be applied to incoming digital video signals so that the signals may be more efficiently compressed by subsequent video compression circuitry. For example, a preprocessor may detect noise in a frame and reduce or remove the noise in the frame before transmitting the frame to the video compression circuitry. Removing noise from digital video signals is not only important for improving the visual quality of the signal, but also for increasing the efficiency of the MPEG video encoders.
Various noise artifacts associated with digital video signals are known in the art. Impulsive noise, also known as salt-and-pepper noise, is defined as individual pixels whose intensity values are much larger or smaller than that of its surrounding neighbors. Often, these impulsive pixels are the result of some type of error or noise and require correction and/or concealment. In some instances, even if the pixel of interest correctly represents the true intensity of a given location at a particular point of time, it is still desirable to treat the impulsive pixel as noise. An example of this is in digital images and video where high frequency content, which includes impulsive pixels, is not only very distracting to a viewer but also very difficult for compression algorithms to effectively compress. The use of bits to compress these impulses takes away bandwidth that could be used more effectively on other parts of the picture. For this reason, a variety of algorithms have been developed in the prior art to reduce and/or remove impulsive noise.
A popular approach to impulsive noise removal is disclosed in “Digital Image Processing” by R. C. Gonzalez and R. E. Woods, Addison_Wesley Publishing Company, 1992, pp. 191-195. Gonzalez and Woods describe a median filter where the median of a set of local neighborhood values is calculated and may be used (adaptively or nonadaptively) to replace the pixel of interest. The median is a value that is both (a) less than half the values in the set and (b) greater than half the values in the set. Referring now to FIG. 5, there is shown an example of neighborhood data where the pixel with intensity value of 99 is the pixel of interest. As an example of median filtering, the 3×5 pixel neighborhood data shown in FIG. 5 contains the values:                (10, 15, 10, 12, 20, 15, 10, 99, 18, 10, 12, 15, 10, 20, 18).        
Sorting these values results in:                (10, 10, 10, 10, 10, 12, 12, 15, 15, 15, 18, 18, 20, 20, 99).        
Therefore, a median filter would use the value of 15 to replace the impulsive value of 99 at the pixel of interest in the center.
One disadvantage of median filtering for both hardware and software implementations is that the calculation of the median requires the neighborhood values to first be sorted. Sorting algorithms not only require computational resources (approximately N*log2 N operations to sort N elements) but may also require additional resources such as memory and code space. Therefore, it is desirable to have a system and method for impulsive noise removal that reduces the necessary computations, thereby resulting in a faster and more efficient method for impulsive removal.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art through comparison of such systems with the present invention as set forth in the remainder of the present application with reference to the drawings.